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Record W2393119087

Effect of Precipitator and Desulphurization Devices on the Removal of Mercury with Different Speciation in Coal-fired Flue Gas

2010· article· en· W2393119087 on OpenAlexaboutno aff
Wenhua Wang

Bibliographic record

VenueEast China Electric Power · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)Flue gasElectrostatic precipitatorFlue-gas desulfurizationBoiler (water heating)CoalWaste managementChemistryCombustionCoal combustion productsEnvironmental chemistryCoal firedPower stationEnvironmental scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

Ontario-Hydro method was employed to determine the concentration and speciation of mercury in the flue-gas emitted from a coal-fired boiler equipped with electrostatic precipitator(ESP) and wet flue gas desulphurization(WFGD).The mass balance of mercury was calculated.The results indicate that HgP could be removed efficiently by ESP.The removal efficiencies of Hg2+、Hg0 and total mercury by WFGD were 81.3%、53.8% and 62.1%,respectively.Mercury mainly emits as Hg0 with a percentage of more than 80% of total mercury.The total mercury balance was 91.17% between the coal and its combustion products.It was verified that the flue-gas cleaning devices of coal-fired power plant had significant impacts on mercury emission characteristics,which could be helpful to develop the integrated technology for precipitator,desulphurization and mercury removal.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.211
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2010
Admission routes1
Has abstractyes

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Same venueEast China Electric PowerSame topicMercury impact and mitigation studiesFrench-language works237,207